def born_rec_w(model, weight, wavelet, rec_coords, space_order=8, isic=False):
"""
Linearized (Born) modeling of a point source for a model
perturbation (square slowness) dm with an extended source
Parameters
----------
model: Model
Physical model
weight: Array
Spatial distriubtion of the extended source
wavelet: Array
Source signature
rec_coords: Array
Coordiantes of the receiver(s)
space_order: Int (optional)
Spatial discretization order, defaults to 8
isic : Bool
Whether or not to use ISIC imaging condition
Returns
----------
Array
Shot record
"""
rec, _, _ = born(model,
None,
rec_coords,
wavelet,
save=False,
ws=weight,
space_order=space_order,
isic=isic)
return rec.data
def born_rec(model, src_coords, wavelet, rec_coords,
space_order=8, free_surface=False, isic=False):
"""
Linearized (Born) modeling of a point source for a model perturbation
(square slowness) dm.
Parameters
----------
model: Model
Physical model
src_coords: Array
Coordiantes of the source(s)
wavelet: Array
Source signature
rec_coords: Array
Coordiantes of the receiver(s)
space_order: Int (optional)
Spatial discretization order, defaults to 8
free_surface: Bool (optional)
Whether or not to use a free surface
isic : Bool
Whether or not to use ISIC imaging condition
Returns
----------
Array
Shot record
"""
rec, _ = born(model, src_coords, rec_coords, wavelet, save=False,
space_order=space_order, free_surface=free_surface, isic=isic)
return rec.data
# Source
f1 = 0.008
src = RickerSource(name='src', grid=model.grid, f0=f1, time=time_axis)
src.coordinates.data[0, :] = np.array(model.domain_size) * 0.5
src.coordinates.data[0, -1] = 20.
# Receiver for observed data
rec_t = Receiver(name='rec_t', grid=model.grid, npoint=301, ntime=nt)
rec_t.coordinates.data[:, 0] = np.linspace(0., 3000., num=301)
rec_t.coordinates.data[:, 1] = 20.
# Linearized data
print("Forward J")
dD_hat, u0l, _ = born(model,
src.coordinates.data,
rec_t.coordinates.data,
src.data,
save=True)
# Forward
print("Forward")
_, u0, _ = forward(model,
src.coordinates.data,
rec_t.coordinates.data,
src.data,
save=True)
# gradient
print("Adjoint J")
dm_hat, _ = gradient(model, dD_hat, rec_t.coordinates.data, u0)
rank = comm.Get_rank()
size = comm.size
#########################################################################################
# Source wavelet
tn = 1000.
dt_shot = model.critical_dt
nt = int(tn / dt_shot)
time_s = np.linspace(0, tn, nt)
wavelet = Ricker(0.015, time_s)
#########################################################################################
# Devito operator
d_obs = born(model, src_coords, rec_coords, wavelet, save=False)[0]
u0 = forward(model, src_coords, rec_coords, wavelet, save=True, t_sub=8)[1]
grad_dist = gradient(model, d_obs, d_obs.coordinates, u0, isic=False)[0]
if rank > 0:
# Send result to master
comm.send(model.m.local_indices, dest=0, tag=10)
comm.send(grad_dist.data, dest=0, tag=11)
else: # Master
# Initialize full array
grad = np.empty(shape=model.m.shape_global, dtype='float32')
grad[model.m.local_indices] = grad_dist.data
# Collect gradients
